ArticleFrontiers in molecular biosciences2022
PON-All: Amino Acid Substitution Tolerance Predictor for All Organisms.
Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed.
- PON-P3: Accurate Prediction of Pathogenicity of Amino Acid Substitutions.International journal of molecular sciences · 2025Article
- Human genomic tools to assess missense variant pathogenicity in domestic mammals using a mock-variant strategy.Open veterinary journal · 2025Article
- There will always be variants of uncertain significance. Analysis of VUSs.NAR genomics and bioinformatics · 2024Article
- PON-Fold: Prediction of Substitutions Affecting Protein Folding Rate.International journal of molecular sciences · 2023Article
- VariBench, new variation benchmark categories and data sets.Frontiers in bioinformatics · 2023Article
- BTKbase, Bruton Tyrosine Kinase Variant Database in X-Linked Agammaglobulinemia: Looking Back and Ahead.Human mutation · 2023Article
- E-SNPs&GO: embedding of protein sequence and function improves the annotation of human pathogenic variants.Bioinformatics (Oxford, England) · 2022Article
- ProTstab2 for Prediction of Protein Thermal Stabilities.International journal of molecular sciences · 2022Article
- Individual Genetic Heterogeneity.Genes · 2022Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genetic variations are investigated in human and many other organisms for many purposes (e.g., to aid in clinical diagnosis). Interpretation of the identified variations can be challenging. Although some dedicated prediction methods have been developed and some tools for human variants can also be used for other organisms, the performance and species range have been limited. We developed a novel variant pathogenicity/tolerance predictor for amino acid substitutions in any organism. The method, PON-All, is a machine learning tool trained on human, animal, and plant variants. Two versions are provided, one with Gene Ontology (GO) annotations and another without these details. GO annotations are not available or are partial for many organisms of interest. The methods provide predictions for three classes: pathogenic, benign, and variants of unknown significance. On the blind test, when using GO annotations, accuracy was 0.913 and MCC 0.827. When GO features were not used, accuracy was 0.856 and MCC 0.712. The performance is the best for human and plant variants and somewhat lower for animal variants because the number of known disease-causing variants in animals is rather small. The method was compared to several other tools and was found to have superior performance. PON-All is freely available at http://structure.bmc.lu.se/PON-All and http://8.133.174.28:8999/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.